Regionalização de vazão mínima em bacias sem dados no semiárido da Bahia
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
dARK ID: | ark:/26339/001300000cq7t |
Texto Completo: | http://repositorio.ufsm.br/handle/1/31745 |
Resumo: | The lack or scarcity of data from hydrological monitoring is one of the major obstacles to the advancement of water resources management and planning. This information is extremely important for the semi-arid, a region that suffers from natural disasters such as extreme droughts, floods and flooding. In this sense, this study aimed to model hydrological variables for basins without data in the semi-arid of Bahia through the regionalization of flows with the Génie Rural model to 4 Paramètres Journalier (GR4J). For this, we used a data set from the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS-BR), which included historical information from 1980 to 2018 in a set of 52 basins. In this study, k-Means and Ward methods were used to group the basins in regions with similar behavior. Within each homogeneous region, the values of the parameters of the model were correlated with physical and hydrogeological characteristics of the basins, in order to obtain the values of the parameters in basins without data, generating equations through linear regression for their determination. The results showed that the k-Means technique was satisfactory for obtaining homogeneous regions and some of the characteristics that influenced the heterogeneity between the clusters and homogeneity within the groups were: the area of the watershed, aridity, the average slope of the basin, the average duration of the maximum precipitation events (number of consecutive days 5 times the average daily precipitation), the average annual evapotranspiration, the longitude, the underground porosity of the watershed, the mean annual precipitation and the median depth of the water table. In general, the models present low efficiency in semi-arid regions, which was not different in this study. In the period analyzed, the GR4J obtained the Nash-Sutcliffe coefficient for the logarithm of flows (Nslog) higher than 70% in 13 (25%) stations in the calibration phase and 7 (13%) in the validation phase. In the process of regionalization of the parameters of the model the linear regression technique was not suitable for obtaining equations. The model was efficient to obtain the reference flow rates with 90% permanence in the historical series (Q90) and the minimum flow rate for seven days of duration with return time (RT) equal to 10 years (Q7,10), presenting a R² greater than 99%. When relating the Q90 obtained through simulated data and observed with the area of the basins, only one of the groups presented P-value lower than 0.05, showing the need to test other methods in order to support decisions regarding the planning and management of water resources in the semi-arid region of Bahia. |
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Regionalização de vazão mínima em bacias sem dados no semiárido da BahiaRegionalization of minimum flow in basins without data in the semi-arid of BahiaBacias sem dadosRegiões homogêneasRegionalização de vazãoSemiáridoGR4JUngauged basinsHomogeneous regionsRegionalization of flowSemi-aridCNPQ::ENGENHARIASThe lack or scarcity of data from hydrological monitoring is one of the major obstacles to the advancement of water resources management and planning. This information is extremely important for the semi-arid, a region that suffers from natural disasters such as extreme droughts, floods and flooding. In this sense, this study aimed to model hydrological variables for basins without data in the semi-arid of Bahia through the regionalization of flows with the Génie Rural model to 4 Paramètres Journalier (GR4J). For this, we used a data set from the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS-BR), which included historical information from 1980 to 2018 in a set of 52 basins. In this study, k-Means and Ward methods were used to group the basins in regions with similar behavior. Within each homogeneous region, the values of the parameters of the model were correlated with physical and hydrogeological characteristics of the basins, in order to obtain the values of the parameters in basins without data, generating equations through linear regression for their determination. The results showed that the k-Means technique was satisfactory for obtaining homogeneous regions and some of the characteristics that influenced the heterogeneity between the clusters and homogeneity within the groups were: the area of the watershed, aridity, the average slope of the basin, the average duration of the maximum precipitation events (number of consecutive days 5 times the average daily precipitation), the average annual evapotranspiration, the longitude, the underground porosity of the watershed, the mean annual precipitation and the median depth of the water table. In general, the models present low efficiency in semi-arid regions, which was not different in this study. In the period analyzed, the GR4J obtained the Nash-Sutcliffe coefficient for the logarithm of flows (Nslog) higher than 70% in 13 (25%) stations in the calibration phase and 7 (13%) in the validation phase. In the process of regionalization of the parameters of the model the linear regression technique was not suitable for obtaining equations. The model was efficient to obtain the reference flow rates with 90% permanence in the historical series (Q90) and the minimum flow rate for seven days of duration with return time (RT) equal to 10 years (Q7,10), presenting a R² greater than 99%. When relating the Q90 obtained through simulated data and observed with the area of the basins, only one of the groups presented P-value lower than 0.05, showing the need to test other methods in order to support decisions regarding the planning and management of water resources in the semi-arid region of Bahia.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESA inexistência ou a escassez de dados provenientes de monitoramento hidrológico é um dos grandes empecilhos para o avanço da gestão e planejamento dos recursos hídricos. Essas informações são extremamente importantes para o semiárido, uma região que sofre com desastres naturais como secas extremas, inundações e alagamentos. Nesse sentido, este estudo teve como objetivo modelar variáveis hidrológicas para bacias sem dados no semiárido da Bahia através da regionalização de vazões com o modelo Génie Rural à 4 Paramètres Journalier (GR4J). Para isso, foi utilizado um conjunto de dados do Catchment Attributes and Meteorology for Large-sample Studies (CAMELS-BR), onde foram englobadas informações históricas do período de 1980 a 2018 em um conjunto de 52 bacias. Neste estudo foram empregados os métodos k-means e Ward para o agrupamento das bacias em regiões com comportamento similar. Dentro de cada região homogênea, os valores dos parâmetros do modelo foram correlacionados com características físicas e hidrogeológicas das bacias, a fim de obter os valores dos parâmetros em bacias sem dados, gerando equações por meio de regressão linear para sua determinação. Os resultados mostraram que a técnica k-means foi satisfatória para a obtenção de regiões homogêneas e algumas das características que influenciaram na heterogeneidade entre os clusters e homogeneidade dentro dos grupos foram: a área da bacia hidrográfica, a aridez, a declividade média da bacia, a duração média dos eventos de precipitação máxima (número de dias consecutivos 5 vezes a precipitação média diária), a evapotranspiração média anual, a longitude, a porosidade subterrânea da bacia hidrográfica, a precipitação média anual e a profundidade mediana do lençol freático. De forma geral, os modelos apresentam baixa eficiência em regiões semiáridas, o que não foi diferente neste estudo. No período analisado, o GR4J obteve o Coeficiente de Nash-Sutcliffe para o logaritmo das vazões (Nslog) superior a 70% em 13 (25%) estações na fase de calibração e 7 (13%) na fase de validação. No processo de regionalização dos parâmetros do modelo a técnica de regressão linear não foi adequada para obtenção de equações. O modelo mostrou-se eficiente para a obtenção das vazões de referência com permanência de 90% na série histórica (Q90) e a vazão mínima referente a setes dias de duração com tempo de retorno (TR) igual a 10 anos (Q7,10), apresentando um R² maior que 99%. Ao relacionar a Q90 obtida por meio de dados simulados e observados com a área das bacias, apenas um dos grupos apresentou P-valor menor que 0,05, evidenciando a necessidade de testar outros métodos no intuito de subsidiar decisões relativas ao planejamento e à gestão dos recursos hídricos no semiárido da Bahia.Universidade Federal de Santa MariaBrasilEngenharia AmbientalUFSMPrograma de Pós-Graduação em Engenharia AmbientalCentro de TecnologiaPiccilli, Daniel Gustavo Allasiahttp://lattes.cnpq.br/3858010328968944Helfer, FernandaBasso, Raviel EuricoSantos, Taiara Sampaio2024-04-11T12:52:52Z2024-04-11T12:52:52Z2023-12-18info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://repositorio.ufsm.br/handle/1/31745ark:/26339/001300000cq7tporAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM2024-04-11T12:52:52Zoai:repositorio.ufsm.br:1/31745Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2024-04-11T12:52:52Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Regionalização de vazão mínima em bacias sem dados no semiárido da Bahia Regionalization of minimum flow in basins without data in the semi-arid of Bahia |
title |
Regionalização de vazão mínima em bacias sem dados no semiárido da Bahia |
spellingShingle |
Regionalização de vazão mínima em bacias sem dados no semiárido da Bahia Santos, Taiara Sampaio Bacias sem dados Regiões homogêneas Regionalização de vazão Semiárido GR4J Ungauged basins Homogeneous regions Regionalization of flow Semi-arid CNPQ::ENGENHARIAS |
title_short |
Regionalização de vazão mínima em bacias sem dados no semiárido da Bahia |
title_full |
Regionalização de vazão mínima em bacias sem dados no semiárido da Bahia |
title_fullStr |
Regionalização de vazão mínima em bacias sem dados no semiárido da Bahia |
title_full_unstemmed |
Regionalização de vazão mínima em bacias sem dados no semiárido da Bahia |
title_sort |
Regionalização de vazão mínima em bacias sem dados no semiárido da Bahia |
author |
Santos, Taiara Sampaio |
author_facet |
Santos, Taiara Sampaio |
author_role |
author |
dc.contributor.none.fl_str_mv |
Piccilli, Daniel Gustavo Allasia http://lattes.cnpq.br/3858010328968944 Helfer, Fernanda Basso, Raviel Eurico |
dc.contributor.author.fl_str_mv |
Santos, Taiara Sampaio |
dc.subject.por.fl_str_mv |
Bacias sem dados Regiões homogêneas Regionalização de vazão Semiárido GR4J Ungauged basins Homogeneous regions Regionalization of flow Semi-arid CNPQ::ENGENHARIAS |
topic |
Bacias sem dados Regiões homogêneas Regionalização de vazão Semiárido GR4J Ungauged basins Homogeneous regions Regionalization of flow Semi-arid CNPQ::ENGENHARIAS |
description |
The lack or scarcity of data from hydrological monitoring is one of the major obstacles to the advancement of water resources management and planning. This information is extremely important for the semi-arid, a region that suffers from natural disasters such as extreme droughts, floods and flooding. In this sense, this study aimed to model hydrological variables for basins without data in the semi-arid of Bahia through the regionalization of flows with the Génie Rural model to 4 Paramètres Journalier (GR4J). For this, we used a data set from the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS-BR), which included historical information from 1980 to 2018 in a set of 52 basins. In this study, k-Means and Ward methods were used to group the basins in regions with similar behavior. Within each homogeneous region, the values of the parameters of the model were correlated with physical and hydrogeological characteristics of the basins, in order to obtain the values of the parameters in basins without data, generating equations through linear regression for their determination. The results showed that the k-Means technique was satisfactory for obtaining homogeneous regions and some of the characteristics that influenced the heterogeneity between the clusters and homogeneity within the groups were: the area of the watershed, aridity, the average slope of the basin, the average duration of the maximum precipitation events (number of consecutive days 5 times the average daily precipitation), the average annual evapotranspiration, the longitude, the underground porosity of the watershed, the mean annual precipitation and the median depth of the water table. In general, the models present low efficiency in semi-arid regions, which was not different in this study. In the period analyzed, the GR4J obtained the Nash-Sutcliffe coefficient for the logarithm of flows (Nslog) higher than 70% in 13 (25%) stations in the calibration phase and 7 (13%) in the validation phase. In the process of regionalization of the parameters of the model the linear regression technique was not suitable for obtaining equations. The model was efficient to obtain the reference flow rates with 90% permanence in the historical series (Q90) and the minimum flow rate for seven days of duration with return time (RT) equal to 10 years (Q7,10), presenting a R² greater than 99%. When relating the Q90 obtained through simulated data and observed with the area of the basins, only one of the groups presented P-value lower than 0.05, showing the need to test other methods in order to support decisions regarding the planning and management of water resources in the semi-arid region of Bahia. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-12-18 2024-04-11T12:52:52Z 2024-04-11T12:52:52Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/31745 |
dc.identifier.dark.fl_str_mv |
ark:/26339/001300000cq7t |
url |
http://repositorio.ufsm.br/handle/1/31745 |
identifier_str_mv |
ark:/26339/001300000cq7t |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Engenharia Ambiental UFSM Programa de Pós-Graduação em Engenharia Ambiental Centro de Tecnologia |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Engenharia Ambiental UFSM Programa de Pós-Graduação em Engenharia Ambiental Centro de Tecnologia |
dc.source.none.fl_str_mv |
reponame:Manancial - Repositório Digital da UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Manancial - Repositório Digital da UFSM |
collection |
Manancial - Repositório Digital da UFSM |
repository.name.fl_str_mv |
Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
atendimento.sib@ufsm.br||tedebc@gmail.com |
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1815172322912370688 |